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Grasp detection is a persistent and intricate challenge with various industrial applications.
Finding antipodal point grasps on irregularly shaped objects
I-Ming Chen and Joel W Burdick · 1993
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Learning to grasp using visual information
Ishay Kamon, Tamar Flash, and Shimon Edelman · 1996
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Michael Gutmann and Aapo Hyvärinen · 2010
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Efficient grasping from rgbd images: Learning using a new rectangle representation
Yun Jiang, Stephen Moseson, and Ashutosh Saxena · 2011
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Deep learning for detecting robotic grasps
Ian Lenz, Honglak Lee, and Ashutosh Saxena · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Preparatory object reorientation for task-oriented grasping
Anh Nguyen, Dimitrios Kanoulas, Darwin G Caldwell, and Nikos G Tsagarakis · 2016
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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
Lerrel Pinto and Abhinav Gupta · 2016
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Towards a rigorous science of interpretable machine learning
Finale Doshi-Velez and Been Kim · 2017
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Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, Michael Laskey, Richard Doan, Xinyu Liu, Juan Aparicio Ojea, and Ken Goldberg · 2017
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Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes
Yu Xiang, Tanner Schmidt, Venkatraman Narayanan, and Dieter Fox · 2017
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Graspnet: An efficient convolutional neural network for real-time grasp detection for low-powered devices
Umar Asif, Jianbin Tang, and Stefan Harrer · 2018
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Jacquard: A large scale dataset for robotic grasp detection
Amaury Depierre, Emmanuel Dellandréa, and Liming Chen · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
Sergey Levine, Peter Pastor, Alex Krizhevsky, Julian Ibarz, and Deirdre Quillen · 2018
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Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach
Douglas Morrison, Peter Corke, and Jürgen Leitner · 2018
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Learning 6-dof grasping interaction via deep geometry-aware 3d representations
Xinchen Yan, Jasmined Hsu, Mohammad Khansari, Yunfei Bai, Arkanath Pathak, Abhinav Gupta, James Davidson, and Honglak Lee · 2018
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A billion ways to grasp: An evaluation of grasp sampling schemes on a dense, physics-based grasp data set
Clemens Eppner, Arsalan Mousavian, and Dieter Fox · 2019
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Lvis: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
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Pointnetgpd: Detecting grasp configurations from point sets
Hongzhuo Liang, Xiaojian Ma, Shuang Li, Michael Görner, Song Tang, Bin Fang, Fuchun Sun, and Jianwei Zhang · 2019
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6-dof graspnet: Variational grasp generation for object manipulation
Arsalan Mousavian, Clemens Eppner, and Dieter Fox · 2019
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Roi-based robotic grasp detection for object overlapping scenes
Hanbo Zhang, Xuguang Lan, Site Bai, Xinwen Zhou, Zhiqiang Tian, and Nanning Zheng · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Graspnet-1billion: A large-scale benchmark for general object grasping
Hao-Shu Fang, Chenxi Wang, Minghao Gou, and Cewu Lu · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Antipodal robotic grasping using generative residual convolutional neural network
Sulabh Kumra, Shirin Joshi, and Ferat Sahin · 2020
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Egad! an evolved grasping analysis dataset for diversity and reproducibility in robotic manipulation
Douglas Morrison, Peter Corke, and Jürgen Leitner · 2020
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End-to-end trainable deep neural network for robotic grasp detection and semantic segmentation from rgb
Stefan Ainetter and Friedrich Fraundorfer · 2021
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Compositional transformers for scene generation
Dor Arad Hudson and Larry Zitnick · 2021
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Fine-grained angular contrastive learning with coarse labels
Guy Bukchin, Eli Schwartz, Kate Saenko, Ori Shahar, Rogerio Feris, Raja Giryes, and Leonid Karlinsky · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Acronym: A large-scale grasp dataset based on simulation
Clemens Eppner, Arsalan Mousavian, and Dieter Fox · 2021
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Synergies between affordance and geometry: 6-dof grasp detection via implicit representations
Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, Kuan Fang, and Yuke Zhu · 2021
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Align before fuse: Vision and language representation learning with momentum distillation
Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong, and Steven Chu Hong Hoi · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
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Legal norm retrieval with variations of the bert model combined with tf-idf vectorization
Sabine Wehnert, Viju Sudhi, Shipra Dureja, Libin Kutty, Saijal Shahania, and Ernesto W De Luca · 2021
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Invigorate: Interactive visual grounding and grasping in clutter
Hanbo Zhang, Yunfan Lu, Cunjun Yu, David Hsu, Xuguang La, and Nanning Zheng · 2021
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Do as i can, not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, et al · 2022
Contrastive diffusion model with auxiliary guidance for coarse-to-fine pet reconstruction
Zeyu Han, Yuhan Wang, Luping Zhou, Peng Wang, Binyu Yan, Jiliu Zhou, Yan Wang, and Dinggang Shen · 2023
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Multimodal fake news detection through data augmentation-based contrastive learning
Jiaheng Hua, Xiaodong Cui, Xianghua Li, Keke Tang, and Peican Zhu · 2023
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Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2023
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Conceptfusion: Open-set multimodal 3d mapping
Krishna Murthy Jatavallabhula, Alihusein Kuwajerwala, Qiao Gu, Mohd Omama, Tao Chen, Shuang Li, Ganesh Iyer, Soroush Saryazdi, Nikhil Keetha, Ayush Tewari, et al · 2023
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Singularity avoidance with application to online trajectory optimization for serial manipulators
Florian Beck, Minh Nhat Vu, Christian Hartl-Nesic, and Andreas Kugi · 2022
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Simvqa: Exploring simulated environments for visual question answering
Paola Cascante-Bonilla, Hui Wu, Letao Wang, Rogerio S Feris, and Vicente Ordonez · 2022
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Fine-grained visual classification using self assessment classifier
Tuong Do, Huy Tran, Erman Tjiputra, Quang D Tran, and Anh Nguyen · 2022
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Metagraspnet: A large-scale benchmark dataset for scene-aware ambidextrous bin picking via physics-based metaverse synthesis
Maximilian Gilles, Yuhao Chen, Tim Robin Winter, E Zhixuan Zeng, and Alexander Wong · 2022
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Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
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Task allocation and planning for product disassembly with human–robot collaboration
Meng-Lun Lee, Sara Behdad, Xiao Liang, and Minghui Zheng · 2022
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Controllable group choreography using contrastive diffusion
Nhat Le, Tuong Do, Khoa Do, Hien Nguyen, Erman Tjiputra, Quang D Tran, and Anh Nguyen · 2023
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Codi: Co-evolving contrastive diffusion models for mixed-type tabular synthesis
Chaejeong Lee, Jayoung Kim, and Noseong Park · 2023
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Text-conditioned sampling framework for text-to-image generation with masked generative models
Jaewoong Lee, Sangwon Jang, Jaehyeong Jo, Jaehong Yoon, Yunji Kim, Jin-Hwa Kim, Jung-Woo Ha, and Sung Ju Hwang · 2023
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Gligen: Open-set grounded text-to-image generation
Yuheng Li, Haotian Liu, Qingyang Wu, Fangzhou Mu, Jianwei Yang, Jianfeng Gao, Chunyuan Li, and Yong Jae Lee · 2023
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Target-referenced reactive grasping for dynamic objects
Jirong Liu, Ruo Zhang, Hao-Shu Fang, Minghao Gou, Hongjie Fang, Chenxi Wang, Sheng Xu, Hengxu Yan, and Cewu Lu · 2023
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Grounding dino: Marrying dino with grounded pre-training for open-set object detection
Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, et al · 2023
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Summary of chatgpt-related research and perspective towards the future of large language models
Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, et al · 2023
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Fedseg: Class-heterogeneous federated learning for semantic segmentation
Jiaxu Miao, Zongxin Yang, Leilei Fan, and Yi Yang · 2023
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Ec2: Emergent communication for embodied control
Yao Mu, Shunyu Yao, Mingyu Ding, Ping Luo, and Chuang Gan · 2023
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Embodiedgpt: Vision-language pre-training via embodied chain of thought
Yao Mu, Qinglong Zhang, Mengkang Hu, Wenhai Wang, Mingyu Ding, Jun Jin, Bin Wang, Jifeng Dai, Yu Qiao, and Ping Luo · 2023
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Deep learning approaches to grasp synthesis: A review
Rhys Newbury, Morris Gu, Lachlan Chumbley, Arsalan Mousavian, Clemens Eppner, Jürgen Leitner, Jeannette Bohg, Antonio Morales, Tamim Asfour, Danica Kragic, et al · 2023
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Open-vocabulary affordance detection in 3d point clouds
Toan Nguyen, Minh Nhat Vu, An Vuong, Dzung Nguyen, Thieu Vo, Ngan Le, and Anh Nguyen · 2023
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Introducing ChatGPT
OpenAI · 2023
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Grasp learning: Models, methods, and performance
Robert Platt · 2023
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Edmp: Ensemble-of-costs-guided diffusion for motion planning
Kallol Saha, Vishal Mandadi, Jayaram Reddy, Ajit Srikanth, Aditya Agarwal, Bipasha Sen, Arun Singh, and Madhava Krishna · 2023
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Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action
Dhruv Shah, Błażej Osiński, brian ichter, and Sergey Levine · 2023
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Llm-planner: Few-shot grounded planning for embodied agents with large language models
Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M Sadler, Wei-Lun Chao, and Yu Su · 2023
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Going denser with open-vocabulary part segmentation
Peize Sun, Shoufa Chen, Chenchen Zhu, Fanyi Xiao, Ping Luo, Saining Xie, and Zhicheng Yan · 2023
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Edge: Editable dance generation from music
Jonathan Tseng, Rodrigo Castellon, and Karen Liu · 2023
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Se (3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
Julen Urain, Niklas Funk, Jan Peters, and Georgia Chalvatzaki · 2023
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Chatgpt for robotics: Design principles and model abilities
Sai Vemprala, Rogerio Bonatti, Arthur Bucker, and Ashish Kapoor · 2023
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Machine learning-based framework for optimally solving the analytical inverse kinematics for redundant manipulators
Minh Nhat Vu, Florian Beck, Michael Schwegel, Christian Hartl-Nesic, Anh Nguyen, and Andreas Kugi · 2023
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Language-driven scene synthesis using multi-conditional diffusion model
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A diffusion model with contrastive learning for icu false arrhythmia alarm reduction
Feng Wu, Guoshuai Zhao, Xueming Qian, and Li-wei Lehman · 2023
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Neurallift-360: Lifting an in-the-wild 2d photo to a 3d object with 360deg views
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A joint modeling of vision-language-action for target-oriented grasping in clutter
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Human-centric scene understanding for 3d large-scale scenarios
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Object-centric inference for language conditioned placement: A foundation model based approach
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Pave the way to grasp anything: Transferring foundation models for universal pick-place robots
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Zero-shot contrastive loss for text-guided diffusion image style transfer
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Grasp-anything: Large-scale grasp dataset from foundation models
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